Charith Perera, Ciaran Mccormick, Arosha Bandara, Blaine A. Price, Bashar Nuseibeh, Privacy-by-Design Framework for Assessing Internet of Things Applications and Platforms, Proceedings of the 6th ACM International Conference on Internet of Things (IoT), Stuttgart, Germany, November, 2016, Pages 83-92
MobiDE’2012, Phoenix, AZ, United States, 20 May, 2012Charith Perera
Charith Perera, Arkady Zaslavsky, Peter Christen, Ali Salehi, Dimitrios Georgakopoulos, Connecting Mobile Things to Global Sensor Network Middleware using System-generated Wrappers, Proceedings of the 11th ACM International Workshop on Data Engineering for Wireless and Mobile Access (ACM SIGMOD/PODS-Workshop-MobiDE), Scottsdale, Arizona, USA, May, 2012
Arkady Zaslavsky, Charith Perera, Dimitrios Georgakopoulos, Sensing as a Service and Big Data, Proceedings of the International Conference on Advances in Cloud Computing (ACC), Bangalore, India, July, 2012, Pages 21-29 (8)
This document summarizes a presentation on improving the sustainability of Internet of Things (IoT) solutions through a trading-based value creation model. The presentation introduces a sensing as a service model where sensor owners can publish sensor data and consumers such as companies can access this data in exchange for offers like discounts or fees. Two surveys found that most respondents viewed this model positively and would be motivated to purchase smart devices. However, open challenges remain regarding technology, economics, social and legal issues. The model aims to increase adoption of IoT solutions in a sustainable way.
Designing Cross-Domain Semantic Web of Things ApplicationsAmélie Gyrard
The document discusses designing cross-domain semantic web of things applications. It introduces challenges including how to interpret IoT data, combine data from different domains, and reuse domain knowledge. The proposed M3 framework addresses these challenges through components like a SWoT generator template, M3 language and ontology, sensor-based linked open rules, and linked open vocabularies for IoT. Evaluations show the framework helps developers build semantic applications and interprets data efficiently while reusing interoperable domain knowledge. The framework has potential applications in domains like health, tourism and transportation.
This document discusses sensitivity analysis of smart meter data for privacy negotiation in IoT applications. It proposes an algorithm to detect sensitive points in smart meter data using kurtosis, Hampel identifier, and modified Rosner filter. The algorithm computes a sensitivity density to quantify privacy. Results on a public dataset show the algorithm detects sensitivity with high accuracy while preserving privacy of appliances like fridges. Future work aims to reduce complexity and improve privacy quantification when analyzing collective energy usage patterns across households.
Assisting IoT Projects and Developers in Designing Interoperable Semantic Web...Amélie Gyrard
Assisting IoT Projects and Developers in Designing Interoperable Semantic Web of Things Applications
The 8th IEEE International Conference on Internet of Things (iThings 2015), 11-13 December 2015, Sydney, Australia
Amelie Gyrard, Christian Bonnet, Karima Boudaoud, Martin Serrano
COMPLEX EVENT PROCESSING USING IOT DEVICES BASED ON ARDUINOijccsa
Complex event processing systems have gained importance since recent developments in communication
and integrated circuits technologies. Developers can easily develop many smart space systems by
connecting various sensors to an Arduino as an internet of thing device. These systems are useful for many
places such as factories, greenhouses (plant house) and smart-homes. Especially in plant houses when the
desired humidity, temperature, light and soil moisture drops the certain level, the users should be notified
through their smartphones. The sensor information is sent to a central server over the internet via an
access point. The collected sensor data needs to be processed online to check whether an event is occurred
or not. The event processing system based on a complex event processing tool is created on the central
server. It is also an important issue to inform mobile users whenever an event occurs. A publish-subscribe
event based system is implemented on the central server. A mobile user is subscribed to the desired event
topic. When an event occurred, which is related with a specific topic, an alarm notification is sent to the
mobile users about the event information so as to take necessary precautions.
30th IEEE International Conference onAdvanced Information Networking and Applications (AINA-2016) March 23-25, 2016, Crans-Montana, Switzerland
Connected Smart Cities: Interoperability with SEG 3.0 for the Internet of Things
Semantic Interoperability
Methodology
Linked Open Data
Linked Open Vocabularies
Linked Open Reasoning
Linked Open Services
Internet of Things
Web of Things
Semantic Web of Things
Smart cities
This document provides an inventory and overview of slide sets related to IoT (Internet of Things) technologies presented by Bob Marcus. It includes links to slide sets on various topics like IoT interfaces, data processing in cyber-physical systems, and IoT use cases. It also lists additional resources like top IoT news sites, Gartner's top 10 IoT technologies for 2017-2018, and a link to an IEEE document discussing technological and social aspects of IoT.
Fog Computing is a paradigm that extends Cloud computing and services to the edge of the network. Similar to Cloud, Fog provides data, compute, storage, and application services to end-users. The motivation of Fog computing lies in a series of real scenarios, such as Smart Grid, smart traffic lights in vehicular networks and software defined networks,
Fog computing is a term created by Cisco that refers to extending cloud computing to the edge of an enterprise's network.
Cisco introduced its fog computing vision in January 2014 as a way of bringing cloud computing capabilities to the edge of the network .
As the result, closer to the rapidly growing number of connected devices and applications that consume cloud services and generate increasingly massive amounts of data.
IRJET -Securing Data in Distributed System using Blockchain and AIIRJET Journal
This document discusses securing data in distributed systems using blockchain and artificial intelligence. It first provides background on increasing data storage needs and security issues as data is shared over networks. It then reviews past research on using blockchain and AI to provide data security. Several studies introduced blockchain-based approaches to improve security in areas like IoT data, public key infrastructure, video surveillance, and decentralized storage. However, most lacked extensive testing or formal verification. The document concludes that combining blockchain for its tamper-proof properties with access control mechanisms could effectively secure sensitive health record data by restricting unauthorized leakage.
This document provides an overview of the Internet of Things (IoT) and introduces DeviceHive as an open-source M2M communication framework for IoT projects. DeviceHive addresses common IoT project problems such as implementing device logic and communication infrastructure by providing libraries, server deployment options, and APIs. It also includes features for device, data, and user management. Examples of using DeviceHive include controlling Philips Hue lights with Google Glass and analyzing energy consumption data for a utility company. The document provides more information on DeviceHive's website and upcoming training events.
IoT-Lite: A Lightweight Semantic Model for the Internet of ThingsPayamBarnaghi
This document presents IoT-Lite, a lightweight semantic model for annotating data in the Internet of Things. IoT-Lite aims to address issues of heterogeneity and interoperability in IoT systems by providing a simple way to semantically describe sensors, actuators, and other devices. It reuses existing models like SSN and defines best practices for annotation. Evaluations show IoT-Lite imposes minimal overhead on data size and query time compared to other semantic models. The goal of IoT-Lite is to make semantic descriptions transparent and easy to implement for both end users and data producers.
ISWC 2016 Tutorial: Semantic Web of Things M3 framework & FIESTA-IoT EU projectFIESTA-IoT
Amelie Gyrard presents a tutorial on SWOT - the Semantic Web of Things.
For further information about this work. Please visit:
http://semantic-web-of-things.appspot.com
The Internet of Things (IoT) is one of the hottest mega-trends in technology – and for good reason , IoT deals with all the components of what we consider web 3.0 including Big Data Analytics, Cloud Computing and Mobile Computing .
Cybersecurity and the Role of Converged Infrastructure June 2016David Rubal, CISSP
1) Government agencies and industries are struggling to upgrade their IT infrastructures to handle the rapidly growing amounts of data, which increases their vulnerability to cybersecurity threats.
2) High-profile data breaches have highlighted the need for agencies to improve data protection. Converged infrastructure, which tightly integrates hardware and software, is emerging as an effective approach.
3) Oracle provides a converged infrastructure solution comprising engineered hardware and software. It argues this approach can help agencies better protect data during processing, computing and storage according to the NIST cybersecurity framework of identifying, protecting, detecting, responding to and recovering from threats.
The document describes an Internet of Things prototype developed by researchers at the University of Calgary to monitor vegetation recovery in northern Alberta. The system uses open source hardware and interoperable IoT standards. It consists of sensor nodes that collect environmental data, a cloud platform that processes and analyzes the data, and a user interface to view the results. The researchers deployed 11 sensor nodes across three boreal forest sites that successfully collected temperature, humidity, and light exposure data and transmitted it to the cloud or stored it locally on microSD cards. The prototype demonstrated the feasibility of using the system for long-term environmental monitoring.
This document discusses research challenges in the Internet of Things (IoT). It begins by defining IoT and describing its key components like sensing, embedded systems, cloud computing, and analytics. It then discusses several application areas like healthcare, automotive, retail, and more. The document outlines the complex IoT architecture involving various stakeholders. It also discusses technical challenges in areas like distributed computing, communication protocols, data storage, analytics, privacy and security. Finally, it provides an overview of Tata Consultancy Services' Innovation Lab in Kolkata, including its research areas, projects, publications, awards and references.
Cytoscape is an open-source software ecosystem for complex network analysis and visualization. It began in 2003 as a Java desktop application but has since expanded to include a REST API, JavaScript library, and Jupyter Notebook/Lab extensions. As an ecosystem, Cytoscape provides domain-independent tools for visualizing and analyzing networks across various fields and computing environments.
Privacy Dynamics: Learning Privacy Norms for Social SoftwareArosha Bandara
Privacy violations in online social networks (OSNs) often arise as a result of users sharing information with unintended audiences. One reason for this is that, although OSN capa- bilities for creating and managing social groups can make it easier to be selective about recipients of a given post, they do not provide enough guidance to the users to make informed sharing decisions. In this paper we present Privacy Dynamics, an adaptive architecture that learns privacy norms for different audience groups based on users’ sharing behaviours. Our architecture is underpinned by a formal model inspired by social identity theory, a social psychology framework for analysing group processes and intergroup relations. Our formal model comprises two main concepts, the group membership as a Social Identity (SI) map and privacy norms as a set of conflict rules. In our approach a privacy norm is specified in terms of the information objects that should be prevented from flowing between two conflicting social identity groups. We implement our formal model by using inductive logic programming (ILP), which automati- cally learns privacy norms. We evaluate the performance of our learning approach using synthesised data representing the sharing behaviour of social network users.
Full Paper: http://oro.open.ac.uk/45951/
Calikli, Gul; Law, Mark; Bandara, Arosha K.; Russo, Alesandra; Dickens, Luke; Price, Blaine A.; Stuart, Avelie; Levine, Mark and Nuseibeh, Bashar (2016). Privacy Dynamics: Learning Privacy Norms for Social Software. In: 11th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, 16-17 May 2016, Austin, Texas, USA, Association of Computing Machinery
SEAMS-2016, 16-17 May, 2016, Austin, Texas, United StatesCharith Perera
Amel Bennaceur, Ciaran McCormick, Jesus Garcia Galan, Charith Perera, Andrew Smith, Andrea Zisman and Bashar Nuseibeh, Feed me, Feed me: An Exemplar for Engineering Adaptive Software, Proceedings of the 11th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS), Austin, Texas, May, 2016, Pages 89-95 (7)
Charith Perera, Saeed Aghaee, Alan Blackwell, Natural Notation for the Domestic Internet of Things , Proceedings of the 5th International Symposium on End-User Development (IS-EUD), Madrid, Spain, May, 2015,
Intel - Copaco Cloud Event 2015 (break-out 3 en 4)Copaco Nederland
Deze presentatie gaat over de impact van ‘Internet of Things’ op de toekomstige samenleving. Elk device krijgt een IP-adres en een processor, zodat mens en machine slimmer en sneller met elkaar kunnen communiceren en we altijd verbonden zijn met de Cloud. Welke kansen biedt dit, en welke uitdagingen moeten we nog tackelen?
More and more organizations are following a Lean model for creating products. This model has been popularized by LeanUX and the Lean Startup movements which emphasize build-test-learn in rapid iterations. This talk (given at Open Web Camp 2012) looks at what has changed in the landscape and the lessons learned in creating user experiences in a lean manner.
Iwsm2014 application of function points to software based on open source - ...Nesma
The document discusses the adaptation of the open source software TRIADE using function point analysis. It presents the methodology used to adapt TRIADE, which involved estimating the lines of code and function points of the original and adapted versions. The results found that adapting TRIADE required around 2,000 function points, which could decrease development efforts by up to 90% compared to building similar software from scratch. However, the analysis has some limitations since conversion factors used to estimate function points have uncertain error margins. Future work should aim to directly measure function points from source code to address these limitations.
This document discusses how to profit from UI-redressing (changing the user interface in a browser). It describes server-side mitigations like X-Frame-Options headers. It recommends targeting CSRF-protected actions and pages with tokens. Various CSS techniques and exploitation methods are outlined, like simple clickjacking and fake captchas. The conclusion encourages profiting from bug bounties by imagining new attack techniques on sites without adequate protections.
Sensing as-a-Service - The New Internet of Things (IOT) Business ModelDr. Mazlan Abbas
Here's a chance to create new business models for Internet of Things. There are tons of benefits to gain from IOT and sensors. Its a matter of time when we can harness the creativity of the IOT Application Developers. Create a healthy eco-system so that everyone benefits.
The document summarizes research from MarketingProfs on effective B2B marketing tactics in 2011. Some key findings include:
- B2B marketing budgets were bouncing back after dropping in 2008-2009, with many companies expecting increased budgets in 2011.
- Generating leads and building brand awareness were top priorities. Traditional tactics were still widely used but online channels like webinars and search marketing were becoming more effective.
- Content marketing strategies, including webinars and optimizing corporate websites, were seen as important ways to generate leads and build brands. Community engagement and influencer marketing were also growing tactics.
apidays LIVE Paris 2021 - The GDPR Developer Guide by Jerome Gorin, CNIL apidays
apidays LIVE Paris 2021 - APIs and the Future of Software
December 7, 8 & 9, 2021
The GDPR Developer Guide : Developping a Data protection culture for Developers
Jerome Gorin, Technologist at CNIL (French National Commission for Informatics and Freedoms)
The document discusses the Internet of Things (IoT) and some of the key challenges. It notes that IoT data is multi-modal, distributed, heterogeneous, noisy and incomplete. It raises issues around data management, actuation and feedback, service descriptions, real-time analysis, and privacy and security. The document outlines research challenges around transforming raw data to actionable information, machine learning for large datasets, making data accessible and discoverable, and energy efficient data collection and communication. It emphasizes that IoT data integration requires solutions across physical, cyber and social domains.
These slides were used at the first Aarhus Follower Group meet-up for the EU-funded project IoTCrawler. They entail an introduction to the project aswell as a more in depth presentation of the difference between web search and Internet of Things (IoT) search an the development of Internet of Things. Furthermore some of the scenarios from the project are presented.
Data Sharing with Sensitive Information Hiding in Data Storage using Cloud Co...ijtsrd
With cloud storage services, users can remotely store their data to the cloud and realize the data sharing with others. Remote data integrity auditing scheme is proposed to guarantee the integrity of the data stored in the cloud. In some common cloud storage systems such as the Electronic Health Records EHRs system, the cloud file might contain some sensitive information. The sensitive information should not be exposed to others when the cloud file is shared. Encrypting the whole shared file can realize the sensitive information hiding, but will make this shared file unable to be used by others. How to realize data sharing with sensitive information hiding in remote data integrity auditing still has not been explored up to now. In order to address this problem, we propose a remote data integrity auditing scheme that realizes data sharing with sensitive information hiding in this system. Paruvathavarthini M | Prasuna K S | Sermakani. A. M ""Data Sharing with Sensitive Information Hiding in Data Storage using Cloud Computing"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-2 , February 2020,
URL: https://www.ijtsrd.com/papers/ijtsrd30007.pdf
Paper Url : https://www.ijtsrd.com/engineering/information-technology/30007/data-sharing-with-sensitive-information-hiding-in-data-storage-using-cloud-computing/paruvathavarthini-m
- Embedded systems now contain sensitive personal data and perform safety-critical functions in devices like mobile phones, cars, and medical equipment. Unless embedded system security is adequately addressed, it could impede adoption.
- There are many challenges to security in embedded systems and IoT devices, including vulnerabilities in hardware, software, and networks. Effective security requires building security in at all stages of the design process.
- Various attacks like physical intrusion, side channel attacks, software exploits, and denial of service attacks threaten embedded systems. Countering these threats requires mechanisms at different levels including prevention, detection, and recovery techniques applied in hardware, software, and networks.
The document proposes a security framework for IoT to address data confidentiality, availability, and integrity. It begins with introducing IoT and discussing its background and threats to data security. A literature review is presented on related work and existing frameworks. The proposed framework includes nine layers: fog computing, management, integrity, security, data analysis, aggregation, storage, archiving, and application. A qualitative model is developed based on the literature review results to capture essential elements for an effective IoT security framework. The research methodology involves a systematic literature review analyzed with qualitative software. The conclusion recommends adopting this framework and its characteristics to better secure IoT data.
SECURITY AND PRIVACY AWARE PROGRAMMING MODEL FOR IOT APPLICATIONS IN CLOUD EN...ijccsa
This document summarizes a research paper on privacy-preserving techniques for IoT data in cloud environments. It introduces two differential privacy algorithms: 1) Generic differential privacy (GenDP) which provides generalized privacy protection for homogeneous and heterogeneous IoT metadata through data portioning. 2) Cluster-based differential privacy which groups similar data into clusters before defining classifiers to validate privacy. The paper evaluates these techniques and finds the cluster-based approach offers better security than customized interactive algorithms while maintaining data utility. Overall, the study presents new differential privacy methods for anonymizing IoT metadata stored in the cloud.
Internet of things (IOT) connects physical to digitalEslam Nader
1) The document discusses the topic of Internet of Things (IoT). It defines IoT as a network of physical objects embedded with sensors that can collect and exchange data.
2) The document outlines some key characteristics of IoT including connectivity, data collection, communication, intelligence, and action. It also discusses how IoT works by collecting data via sensors, communicating data through networks, analyzing the data, and taking action.
3) Several potential research topics in IoT are proposed, including applying deep learning for intrusion detection in IoT networks, finding dead zones in large IoT networks, and developing governance models for machine learning algorithms within IoT.
Open Source Platforms Integration for the Development of an Architecture of C...Eswar Publications
The goal of the Internet of Things (IoT) is to achieve the interconnection and interaction of all kind of everyday
objects. IoT architecture can be implemented in various ways. This paper presents a way to mount an IoT architecture using open source hardware and software platforms and shows that this is a viable option to collect information through various sensors and present it through a web page.
Fog computing is a system-level architecture that distributes computing, storage, control and networking functions closer to users along the continuum between IoT devices and the cloud. It aims to address issues like high latency and network congestion that result from processing all IoT data in the cloud. Key characteristics of fog computing include its ability to support location awareness, mobility and real-time interactions through a geographically distributed deployment.
Semantic Technologies for the Internet of Things: Challenges and Opportunities PayamBarnaghi
The document discusses semantic technologies for the Internet of Things (IoT), outlining both challenges and opportunities. It notes that IoT data is heterogeneous, distributed, noisy, incomplete, time and location dependent, and dynamic. Semantic descriptions could help address issues of interoperability and machine interpretability, but real-world implementation faces challenges of complexity versus expressiveness, where and how to publish semantics, and handling dynamic data meanings. Simplicity is important, and semantics should be designed with the intended uses and users in mind. Semantics are an intermediary that must effectively enable tools, APIs, querying, and data analysis to be useful for applications.
Cloud Forensics: Drawbacks in Current Methodologies and Proposed SolutionIJERA Editor
The document summarizes research on cloud forensics and proposes a new framework. It discusses drawbacks in current cloud forensics methodologies, including an inability to collect evidence from all cloud subscribers and support future forensic objectives. The proposed framework aims to offer a forensic-friendly cloud platform that facilitates easy access to cloud evidence in a forensically-sound manner while minimizing non-essential data and maximizing reliability, relevance and authenticity of collected evidence.
The Internet of things describes physical objects that are embedded with sensors, processing ability, software, and other technologies that connect and exchange data with other devices and systems over the Internet or other communications networks.
Big Data in Distributed Analytics,Cybersecurity And Digital ForensicsSherinMariamReji05
This document provides an overview of big data and its applications in distributed analytics, cyber security, and digital forensics. It discusses how big data can reduce the processing time of large volumes of data in distributed computing environments using Hadoop. Examples of big data applications include using social media, search engine, and aircraft black box data for analysis. The document also outlines the challenges of traditional systems and how distributed big data architectures help address them by allowing data to be processed across clustered computers.
This document proposes a system for personal and community context discovery as a service. It suggests using mobile phone sensors, 3D cameras, and web data in a non-intrusive way to gather information on location, proximity, activity, and identity to discover individual behaviors and community patterns. A multimodal fusion approach is recommended to integrate these context sources for improved accuracy. An IoT platform is presented as a way to implement and deploy this context discovery service for application developers.
Dynamic Data Analytics for the Internet of Things: Challenges and OpportunitiesPayamBarnaghi
Dynamic Data Analytics for the Internet of Things: Challenges and Opportunities
IoT data analytics faces unique challenges compared to traditional big data analytics. IoT data is multi-modal, heterogeneous, noisy, incomplete, time and location dependent, and dynamic. It requires near real-time analysis while ensuring privacy and security. Analyzing IoT data requires an ecosystem approach that can integrate data from multiple sources and platforms semantically. Discovery engines are needed to locate IoT data streams and resources that are often mobile and transient. Context-aware and opportunistic techniques are required to access and route IoT data. The goal is to extract insights and actionable knowledge from physical, cyber, and social data sources.
This document discusses applying privacy preserving data mining techniques to code profiling data. Code profiling generates metrics about software attributes and performance. The author applies encryption to code profiling data from 140 Java codes to preserve privacy. K-means clustering and k-NN classification are performed on the actual and encrypted data, showing similar results while preserving privacy. Correlation analysis identifies weakly correlated attributes that are removed to improve clustering accuracy, though this decreases classifier accuracy. The paper concludes privacy preserving data mining of code profiling data is an emerging area that could benefit from additional encryption and classification techniques.
The document provides an overview of various digital technologies including AI, IoT, cloud computing, data analytics, and more. It discusses the "apples" or fundamental technologies in these areas like AR, VR, AI, IoT, and cloud computing. It then outlines several learning paths one could take to understand these technologies, beginning with foundations in areas like probability, statistics, computer science, and communications. It provides recommendations for books and courses to learn about each technology from roots to more advanced concepts. Finally, it discusses bringing all the pieces together using design thinking.
Complexity of IOT/IOE Architectures for Smart Service Infrastructures Panel:...Paolo Nesi
The complexity of smart and sentient applications in smart cities is progressively increasing.
to reach higher precision.
time series prediction artificial intelligent, machine learning
Single data sets multi data sets, and big data: addressing heterogeneity, low quality and discontinuity, etc.
integration of open data, real time data and private IOT / personal data is increasing complexity of cyber-physical-social aspects:
to have the full control on the rights associated to their content
GDPR normative (since May 2018 in force) to regulate the access and control of privacy
I am bringing the experience of addressing
GDPR and Security and into Smart City Solutions with IOT
-----smart city impact----------------
Signed Consent vs Informed Consent
Smart Applications exploit personal data about (for example)
user position and actions for providing geolocated suggestions
home/work position, trajectories,
Payments and traces from bike sharing, from navigators, etc.
body signals/data for monitoring healthiness (glucose, temperature, etc.), for training sport, ..
User actions on applications: choices on menu, queries performed, mobile phones, requested paths, payments, etc.
IOT Devices data: mobile, buttons, trackers, but also temperature in house; position of our dogs, children, cars, bikes, …
etc.
----GDPR: General Data Protection Regulation ---
Users are going to decide to:
provide access to who, for do what, until we consent
accept terms of use by signed consent for each data management service, before was a simple informed consent
from each service, the user has to be capable to
See what the provider collect in terms of its Data Type: traces, logs, paths, profiles, accesses, IOT devices, sensors, maps, etc.
Download, delete, inspect each single Data Type
Auditing and Revoke access or grant access right to each single Data Type
Delete all Data Types in single shot or singularly (forget all about me)
Similar to IOT-2016 7-9 Septermber, 2016, Stuttgart, Germany (20)
OCS Training Institute is pleased to co-operate with
a Global provider of Rig Inspection/Audits,
Commission-ing, Compliance & Acceptance as well as
& Engineering for Offshore Drilling Rigs, to deliver
Drilling Rig Inspec-tion Workshops (RIW) which
teaches the inspection & maintenance procedures
required to ensure equipment integrity. Candidates
learn to implement the relevant standards &
understand industry requirements so that they can
verify the condition of a rig’s equipment & improve
safety, thus reducing the number of accidents and
protecting the asset.
20CDE09- INFORMATION DESIGN
UNIT I INCEPTION OF INFORMATION DESIGN
Introduction and Definition
History of Information Design
Need of Information Design
Types of Information Design
Identifying audience
Defining the audience and their needs
Inclusivity and Visual impairment
Case study.
Response & Safe AI at Summer School of AI at IIITHIIIT Hyderabad
Talk covering Guardrails , Jailbreak, What is an alignment problem? RLHF, EU AI Act, Machine & Graph unlearning, Bias, Inconsistency, Probing, Interpretability, Bias
Understanding Cybersecurity Breaches: Causes, Consequences, and PreventionBert Blevins
Cybersecurity breaches are a growing threat in today’s interconnected digital landscape, affecting individuals, businesses, and governments alike. These breaches compromise sensitive information and erode trust in online services and systems. Understanding the causes, consequences, and prevention strategies of cybersecurity breaches is crucial to protect against these pervasive risks.
Cybersecurity breaches refer to unauthorized access, manipulation, or destruction of digital information or systems. They can occur through various means such as malware, phishing attacks, insider threats, and vulnerabilities in software or hardware. Once a breach happens, cybercriminals can exploit the compromised data for financial gain, espionage, or sabotage. Causes of breaches include software and hardware vulnerabilities, phishing attacks, insider threats, weak passwords, and a lack of security awareness.
The consequences of cybersecurity breaches are severe. Financial loss is a significant impact, as organizations face theft of funds, legal fees, and repair costs. Breaches also damage reputations, leading to a loss of trust among customers, partners, and stakeholders. Regulatory penalties are another consequence, with hefty fines imposed for non-compliance with data protection regulations. Intellectual property theft undermines innovation and competitiveness, while disruptions of critical services like healthcare and utilities impact public safety and well-being.
How to Manage Internal Notes in Odoo 17 POSCeline George
In this slide, we'll explore how to leverage internal notes within Odoo 17 POS to enhance communication and streamline operations. Internal notes provide a platform for staff to exchange crucial information regarding orders, customers, or specific tasks, all while remaining invisible to the customer. This fosters improved collaboration and ensures everyone on the team is on the same page.
this slide shows husien hanafy portfolio 6-2024hessenhanafy1
Highly Motivated architectural engineer with 6 years of experience in interior, exterior, and landscape design, I'm self-motivated person and a competitive professional who is driven by goals with complete dedication and enthusiasm
Enhancing Security with Multi-Factor Authentication in Privileged Access Mana...Bert Blevins
In the constantly evolving field of cybersecurity, ensuring robust protection for sensitive data and critical systems has never been more vital. As cyber threats grow more sophisticated, organizations continually seek innovative ways to bolster their defenses. One of the most effective tools in the security arsenal is Multi-Factor Authentication (MFA), particularly when integrated with Privileged Access Management (PAM).
Privileged Access Management encompasses the methods, procedures, and tools used to regulate and monitor access to privileged accounts within an organization. Users with privileged accounts possess elevated rights, enabling them to perform essential operations such as system configuration, access to sensitive data, and management of network infrastructure. However, these elevated privileges also pose a significant security risk if they fall into the wrong hands.
By combining MFA with PAM, organizations can significantly enhance their security posture. MFA adds an additional layer of verification, ensuring that even if privileged account credentials are compromised, unauthorized access can be thwarted. This integration of MFA and PAM provides a robust defense mechanism, protecting critical systems and sensitive data from increasingly sophisticated cyber threats.
Enhancing Security with Multi-Factor Authentication in Privileged Access Mana...
IOT-2016 7-9 Septermber, 2016, Stuttgart, Germany
1. Privacy-‐by-‐Design Framework
for
Assessing
Internet
of
Things
Applications
and
Platforms
Charith
Perera,
Ciaran
McCormick,
Arosha
K.
Bandara,
Blaine
Price,
Bashar
Nuseibeh
The
6th
International
Conference
on
the
Internet
of
Things
(IoT
2016)
November
7–9,
2016
in
Stuttgart,
Germany.
2. Internet
of
Things
• The
Internet
of
Things
(IoT)
is
“…the
network
of
physical
objects—
devices,
vehicles,
buildings
and
other
items—embedded
with
electronics,
software,
sensors,
and
network
connectivity
that
enables
these
objects
to
collect
and
exchange
data…”#
• By
2020,
there
will
be
50
to
100
billion
devices
(i.e.
things,
sensors,
smart
objects)
connected
to
the
Internet*
#
International
Telecommunication
Union,
Internet
of
Things
Global
Standards
Initiative,
2015,
http://www.itu.int/en/ITU-‐T/gsi/iot/Pages/default.aspx
*
International
Data
Corporation
(IDC)
Corporate
USA,
“Worldwide
smart
connected
device
shipments,”
March
2012,
http://www.idc.com/getdoc.jsp?containerId=prUS23398412
3. Application
Development
Desktop
Application
Mobile
Application
Web
Application
Application
• Processing
happens
locally
• UI
sits
locally
• Processing
happens
locally
complemented
by
cloud
resources
• UI
sits
locally
• Processing
happens
remotely
• UI
sits
locally
4. Internet
of
Things
Application
Development
BeagleBone
Waspmote
Raspberry PiArdunio
Gadgeteer
Dragonboard 410C
• NO Operating System
• Less Powerful
• OS Driven
• More Powerful
Cloud Computing
• Unlimited Computational
Resources*
6. Privacy-‐by-‐Design
• IoT
applications
are
complex
by
nature
as
they
involve
both
software
and
hardware
as
well
as
many
different
types
of
computational
devices
(e.g.,
sensors,
gateways,
cloud)
• Privacy
is
a
significant
problem
in
IoT
applications
because
they
handle
data
that
can
be
used
to
derive
very
sensitive
personal
information
7. Why
hasn’t
privacy
been
a
priority?
• IoT
systems
(applications,
service,
platforms)
are
still
new;
Not
mature
enough
• Most
IoT
platforms
follow
the
philosophy
“You
feed
your
data
to
our
platform,
we
do
the
processing
and
give
you
back
the
results”
• Current
IoT
platform
providers
assume,
anyone
who
uses
their
platform
has
the
full
ownership
of
the
data
they
feed.
(In
reality
this
is
not
the
case
always)
• Therefore,
privacy
is
not
a
major
concern
for
IoT
platform
providers.
8. Our
Motivation
and
Proposed
solution
• There
isn’t
any
process/methodology/framework
to
help
software
architects
in
assessing
and
designing
IoT
applications
• Existing
frameworks
are
not
prescriptive
enough
to
follow
by
an
engineer
(We
discuss
them
few
slides
later)
• Recent
Security
and
Privacy
Violations:
HACKING
IoT:
A
Case
Study
on
Baby
Monitor
Exposures
and
Vulnerabilities#
• Therefore,
we
wanted
to
build
a
Privacy-‐by-‐design
framework
that
can
guide
software
architects
in
assessing
IoT
application.
#
https://www.rapid7.com/docs/Hacking-‐IoT-‐A-‐Case-‐Study-‐on-‐Baby-‐Monitor-‐Exposures-‐and-‐Vulnerabilities.pdf
9. BUT
IT
IS
NOT
….
• Guidelines
SHOULD
NOT
be
used
to
compare
different
IoT
application
or
platforms.
• The
primary
reason
is
that
each
IoT
application
or
platforms
is
designed
to
serve
a
specific
purpose
or
category
of
application.
Focus:
Enterprise
middleware
platform
for
Smart
Cities
and
Businesses
Focus:
Smart
Home
Automation
10. What
is
out
there
?
(Literature)
Privacy
by
Design
Foundational
Principles
-‐ Ann
Cavoukian*
1) Proactive
not
reactive;
preventative
not
remedial
2) Privacy
as
the
default
setting
3) Privacy
embedded
into
design
4) Full
functionality
positive-‐sum,
not
zero-‐sum
5) End-‐to-‐end
security-‐full
life-‐cycle
protection
6) Visibility
and
transparency-‐ keep
it
open
7) Respect
for
user
privacy,
keep
it
user-‐centric
*A.
Cavoukian,
“Resolution
on
privacy
by
design,”
in
32nd
International
Conference
of
Data
Protection
and
Privacy
Commissioners,
2010.
11. What
is
out
there
?
(Literature)
LINDDUN
– Deng
et
al.*
*M.
Deng,
K.
Wuyts,
R.
Scandariato,
B.
Preneel,
and
W.
Joosen,
“A
privacy
threat
analysis
framework:
supporting
the
elicitation
and
fulfillment of
privacy
requirements,”
Requirements
Engineering,
vol.
16,
no.
1,
pp.
3–32,
2011.
This
is
a
privacy
threat
analysis
framework
that
uses
data
flow
diagrams
(DFD)
to
identify
privacy
threats.
1) Define
the
DFD
2) Map
privacy
threats
to
DFD
elements
3) Identify
threat
scenarios
4) Prioritize
threats
5) Elicit
mitigation
strategies
6) Select
corresponding
PETS
12. What
is
out
there
?
(Literature)
*J.-‐H.
Hoepman,
"Privacy
Design
Strategies,"
in
ICT
Systems
Security
and
Privacy
Protection,
vol.
428,
N.
Cuppens-‐Boulahia,
F.
Cuppens,
S.
Jajodia,
A.
Abou El
Kalam and
T.
Sans,
Eds.,
Springer
Berlin
Heidelberg,
2014,
pp.
446-‐459.
Privacy
Design
Strategies
–Hoepman*
1) Minimize
2) Hide
3) Separate
4) Aggregate
5) Inform
6) Control
7) Enforce
8) Demonstrate
• We
determined
that
Hoepman’s
is
the
most
appropriate
starting
point
for
developing
a
more
detailed
privacy-‐by-‐design
• Primarily
because
this
framework
already
focuses
on
the
architectural
aspects
of
privacy
design
13. IoT
Data
Flow
View
CDA
DPP
DPADS
DD
CDA
DPP
DPADS
DD
CDA
DPP
DPADS
DD
CDA
DPP
DPA
DS
DD
Consent
and
Data
Acquisition
Data
Pre-‐Processing
Data
Processing
and
Analysis
Data
Storage
Data
Dissemination
14. Privacy
By
Design
Guidelines
1) Minimise data acquisition
2) Minimise number of data sources
3) Minimise raw data intake
4) Minimize knowledge discovery
5) Minimize data storage
6) Minimize data retention period
7) Hidden data routing
8) Data anonymization
9) Encrypted data communication
10) Encrypted data processing
11) Encrypted data storage
12) Reduce data granularity
13) Query answering
14) Repeated query blocking
15) Distributed data processing
16) Distributed data storage
17) Knowledge discovery based aggregation
18) Geography based aggregation
19) Chain aggregation
20) Time-Period based aggregation
21) Category based aggregation
22) Information Disclosure
23) Control
24) Logging
25) Auditing
26) Open Source
27) Data Flow Diagrams (DFD)
28) Certification
29) Standardization
30) Compliance with Policy, Law, Regulations
MINIMISEHIDESEPARATE
AGGREGATIONDEMONSTRATE
INFORM
CONTROL
/
ENFORCE
15. Evaluation
of
Privacy
Capabilities:
Methodology
• Step
1:
Identify
how
data
flows
in
the
existing
application
or
platform
• Step
2:
Build
a
table
for
each
node
where
columns
represent
data
life
cycle
phases
and
rows
represent
each
privacy-‐by-‐design
guideline.
• Step
3:
Depending
on
the
level
of
detail
which
software
architects
wish
to
explore,
they
can
either
use
(1)
a
summarised
colour
coding
base
scheme
(2)
a
notes
based
scheme
17. Platforms
We
Assessed
http://www.eclipse.org/smarthome/ https://github.com/OpenIotOrg/openiot
• Focus:
Enterprise
middleware
platform
for
Smart
Cities
and
Businesses
• Middleware
infrastructure
supports
flexible
configuration
and
deployment
of
algorithms
for
collecting,
and
filtering
information
streams
stemming
from
internet
connected
objects
• Focus:
Smart
Home
Automation
• Platform
for
integrating
different
home
automation
systems
and
technologies
into
one
single
solution
that
allows
over-‐
arching
automation
rules
and
uniform
user
interfaces
19. Research
Directions
• Can
1)
Novice
2)
Experience
Software
architects
assess
a
given
platform
using
the
proposed
guidelines
consistently?
If
there
are
variation,
why?
• Given
a
case
study,
can
privacy
guidelines
guide
1)
Novice
2)
Experience
Towards
a better privacy-‐aware
IoT
applications
Evaluation
Future
work
• Privacy
Tactics
-‐ Tactics
are
design
decisions
that
improve
individual
quality
attribute
(e.g.
Privacy)
concerns.
[Basic
building
blocks]
• Privacy
Patterns
-‐ Patterns describe
the
high-‐level
structure
and
behaviour
of
software
systems
as
the
solution
to
multiple
system
requirements
[Complex
Compositions]